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Ghasemian et al., 2018


The relative sensitivity of forest productivity to landscape position vs. microtopography

Ghasemian, S., J. Kastens, S.A. Billings (2018)
American Geophysical Union 2018 Fall Meeting, Washington, DC, 10-14 Dec 2018  


Both landscape position (i.e. relative elevation) and small-scale topography (i.e. meters to tens of meters) influence forest primary productivity, because topography influences moisture and nutrient availability. However, conditions governing the relative importance of macro- vs. microtopography remain unclear. We assess the influence of microtopography on forest productivity relative to landscape position as moisture availability changes across time, how this effect depends on aspect, and microtopographical influence on forest recovery from drought. Using Enhanced Vegetation Index as a proxy for productivity in a ~638 ha watershed in the Calhoun Critical Zone Observatory, we estimate how productivity in forest regenerating post-agriculture varies across time with elevation, microtopographical position, and aspect. EVI values were obtained from LandSat images (30m^2 pixels) from 1984 to 2017. Elevation and aspect were assigned to each pixel based on a Digital Elevation Model. We quantified each pixel’s microtopographical position relative to its surroundings as the difference between its elevation and the average elevation of surrounding pixels. Forest productivity was greater at lower elevations, as might be predicted given typically greater moisture and nutrient availability downslope. However, microtopography– the position of land relative to its immediate surroundings– was a more robust predictor of productivity than elevation. Specifically, productivity was generally higher in pixels at lower elevation than surrounding pixels, regardless of landscape position within the larger watershed. An exception to this was when moisture shortage limited productivity. Then, contrary to our hypothesis, this relationship was reversed, for reasons that remain unclear. Microtopographical position was a weaker predictor of productivity on south-facing slopes, which exhibited some of the lowest productivity and likely are subjected to greater water stress in some years. Our work highlights how linking remote sensing data in novel ways to microtopographical features can reveal determinants of ecosystem productivity, and how these effects can vary with moisture availability in unexpected ways.


Ghasemian, S., J. Kastens, S.A. Billings (2018): The relative sensitivity of forest productivity to landscape position vs microtopography. American Geophysical Union 2018 Fall Meeting, Washington, DC, 10-14 Dec 2018.

This Paper/Book acknowledges NSF CZO grant support.